An automated analysis of structured electronic data, such as in a data warehouse, which is intended to discover previously unrecognized patterns and relationships between data items. It differs from OLAP and other forms of query-driven data analysis in that patterns are determined by the system using statistical algorithms, thereby uncovering relationships for which the user hasn't developed a query. Human analysis of the statistical patterns is then required to determine the reasons for the emerging relationships.
Related categories 10
Data Mining and Knowledge Discovery
A peer-reviewed journal publishing articles on all aspects of Knowledge Discovery in Databases (KDD) and data mining methods for extracting high-level representations (patterns and models) from data. Accepts submissions of original research or technical survey articles of related fields and techniques.
Data Mining on the Web
Article by Dan Greening on data mining techniques applied to analyzing and making decisions from web data.
Estimating Campaign Benefits and Modeling Lift (Overheads)
In assessing the potential of data mining based marketing campaigns one needs to estimate the payoff of applying modeling to the problem of predicting behavior of some target population. We present a methodology for initial cost/benefit analysis and present surprising empirical results, based on actual business data from several domains, on achievable model accuracy.
Kurt Thearling: Data Mining and CRM
Information on data mining and CRM technology. Includes a list of reference books, together with articles and white papers.
Digging Up Dollars with Data Mining - An Executive's Guide
Tim Graettinger. Data mining creates information assets that an organization can leverage to achieve these strategic objectives. In this article, we address some of the key questions executives have about data mining. (September 01, 1999)
Last update:July 18, 2016 at 19:05:44 UTC